woman searching on smartphone next to robot graffiti
PHOTO: Shane Rounce

If you haven't applied artificial intelligence (AI) to any part of your CX program, you're already late to the party. But late adopters stand to benefit from the mistakes and learnings of others.

Early adopters to AI in customer experience have paved the way for later adopters. The success stories are out there. The simple customer engagements being managed by AI today are delivering ROI in the blink of an eye, and brands have created models to easily identify many KPIs such as “likelihood to churn,” “recommend,” “buy more” or “buy less.” I call this first stage “AI for in the moment customer experience.”

The second stage I call “AI for prediction.” AI for prediction is a great management tool for change and forecasting. We're seeing rapid adoption and growth in this area and for latecomers, this is where you may see the biggest business impact — with fast ROI indicators driving rapid change management.

Your business has the opportunity to move quickly to the next base, which can help understand what your customer pain points are and how much these will cost or create for you over the year ahead. Knowledge like this helps you make business-critical operational decisions regarding major products or services so you can stay ahead of customer wants and needs.

Let’s take a look at why AI is important and what benefits you may be missing out on.

What Does AI Bring to Customer Experience?

AI is transforming the CX playing field from fixed point customer data collection and processing to a new agile and personalized experience.

Many aspects of customer experience can be either handled or led by AI: from a marketing-led customer entry point of the funnel to seamless engagements offering personalized product and service selections, complementary additional offerings, preferred fulfillment route and after-sales service wrapped in a neat loyalty bow. If you are interested in higher customer acquisition conversion rates, increased lifetime value and a lower cost-to-serve, there is a good reason to invest strongly in AI this coming year.

Related Article: Where AI Customer Experience Investments Are Paying Off

Where Do I Start?

Broadly speaking, those that have been collecting signals across channels already have a head start, as they've likely either deployed or are in the process of procuring some fundamental AI engagement software or services. Being able to connect those signals into a journey overview becomes a number one task pretty quickly.

Many organizations start with self-service as their first AI-driven initiative. What they find is that many customers, wherever possible, like the option to serve themselves and that AI is a relatively cost-effective way to deliver those engagements across certain key channels.

Related Article: Where Self-Service Ends and Direct Customer Support Begins

Real-Time AI in Digital Customer Journeys

Chatbots and virtual assistants are the new breed of digital support. But there's a significant difference between the two, with chatbots generally more useful in predictable conversations and managing simple, automated tasks. Virtual assistants, on the other hand, can perform a range of tasks such as: comparing products; finding the best product based on the given features; or taking into account a customer’s previous purchase to help predict future purchase or next best action. Unlike chatbots, virtual assistants typically mature and learn over time, so their value to the customer and business will naturally increase.

Analytics solutions can trigger virtual assistants or chatbots to directly engage with a customer after recognizing behaviors such as confusion or distress. The chatbot or virtual  assistant can then offer to help reroute the customer to the correct part of the website to complete their goal or to an FAQ to learn more. If the assistant cannot answer a request, they simply route the customer to another channel such as a live chat advisor. AI assistant engagements can also be automatically triggered at known points of pain to help a customer complete a goal or journey, and can be a great method to drive down deflection to the contact center.

Related Article: What Makes a Chatbot Tick?

AI in the Contact Center

AI is helping replace those lengthy and confusing IVR maps that customers have to navigate. Simply by using natural language processing, customers can speak the reason for their call and be automatically looped to either a live human agent for a complex matter or to a virtual assistant for a task-oriented engagement like balance inquiry or password reset.

One of the greatest advancements for CX in the contact center is customer analytics solutions. These can create beautiful real-time dashboards for agents to drive next-best actions while they are either helping customers live or segmenting customers to re-engage according to predictive algorithms. Imagine how powerful it would be if based on the behavior of the few, you could predict the actions of many. This could allow you to segment and proactively reach out to customers with highly relevant offers or make very personal customer saves at scale.

AI brings value across the customer journey, but the overarching view is greater than the sum of its parts. It is now possible to pull together a customer journey view which has crossed more than one channel,  identifying a single customer with different IDs across these channels. Once you can identify a single journey, you can identify whole customer segments taking that same journey and rapidly see where the key drop-offs are and the reasons behind those droff-offs. Simultaneously, you can apply metrics such as net promoter score to determine the value of a successful journey for a “promoter” versus the value of the same successful journey of a “passive” or “detractor.” If your business does not know the monetary value of your customer journeys yet, whether successful or otherwise, you should be looking at this now.